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Prompt engineering for zero‐shot and few‐shot defect detection and classification using a visual‐language pretrained model

Author(s): ORCID (Building Informatics Group, Department of Architecture and Architectural Engineering Yonsei University Seoul South Korea)
(Building Informatics Group, Department of Architecture and Architectural Engineering Yonsei University Seoul South Korea)
(Building Informatics Group, Department of Architecture and Architectural Engineering Yonsei University Seoul South Korea)
(Building Informatics Group, Department of Architecture and Architectural Engineering Yonsei University Seoul South Korea)
Medium: journal article
Language(s): English
Published in: Computer-Aided Civil and Infrastructure Engineering, , n. 11, v. 38
Page(s): 1536-1554
DOI: 10.1111/mice.12954
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1111/mice.12954.
  • About this
    data sheet
  • Reference-ID
    10696412
  • Published on:
    12/12/2022
  • Last updated on:
    02/09/2023
 
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